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Direct linkMichael Nagel; Lukas Fischer; Tim Pawlowski; Augustin Kelava – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Bayesian estimations of complex regression models with high-dimensional parameter spaces require advanced priors, capable of addressing both sparsity and multicollinearity in the data. The Dirichlet-horseshoe, a new prior distribution that combines and expands on the concepts of the regularized horseshoe and the Dirichlet-Laplace priors, is a…
Descriptors: Bayesian Statistics, Regression (Statistics), Computation, Statistical Distributions
